• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1483-1495
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• 2007

Thanks to IEEE 802.11 technique, accessing Internet through a wireless LAN(Local Area Network) is possible in the most of the places including university campuses, shopping malls, offices, hospitals, stations, and so on. Most of the APs(access points) for wireless LAN are supporting 2.4 GHz band 802.11b and 802.11g protocols. This paper is introducing a C# library function which can be used to read RSSIs(Received Signal Strength Indicator) from APs. An LBS(Location Based Service) estimates the current location of the user and provides useful user's location-based services such as navigation, points of interest, and so on. Therefore, indoor, LBS is very desirable. However, an indoor LBS cannot be realized unless indoor position ing is possible. For indoor positioning, techniques of using infrared, ultrasound, signal strength of UDP packet have been proposed. One of the disadvantages of these techniques is that they require special equipments dedicated for positioning. On the other hand, wireless LAN-based indoor positioning does not require any special equipments and more economical. A wireless LAN-based positioning cannot be realized without reading RSSIs from APs. Therefore, our C# library function will be widely used in the field of indoor positioning. In addition to providing a C# library function of reading RSSI, this paper introduces implementation of indoor positioning modules making use of the library function. The methods used in the implementation are K-NN(K Nearest Neighbors), Bayesian and trilateration. K-NN and Bayesian are kind of fingerprinting method. A fingerprint method consists of off-line phase and realtime phase. The process time of realtime phase must be fast. This paper proposes a decision tree method in order to improve the process time of realtime phase. Experimental results of comparing performances of these methods are also discussed.